A Survey of UAS Technologies to Enable Beyond Visual Line Of Sight

(BVLOS) Operations

Elena Politi

, Ilias Panagiotopoulos

, Iraklis Varlamis

and George Dimitrakopoulos

Department of Informatics and Telematics, Harokopio University of Athens, Greece

Keywords:

Beyond Visual Line Of Sight (BVLOS) Operations, UAV, UAS, Drone Technologies, Requirements.

Abstract:

Latest trends, societal needs and technological advances have led to an unparalleled expansion in the use

of Unmanned Aerial Systems (UAS) for versatile civilian and military applications, ranging from simple

everyday operations, to the supervision in construction sites, even logistics, among others. Unmanned Aerial

Vehicles (UAVs), widely known as drones, are the main components of UAS, and are becoming increasingly

popular in such operations, since they reduce costs, they facilitate activities and can increase the granularity of

surveillance or delivery. Furthermore, they can pave new ways for the implementation of smart-sensing and

navigation functionalities, support automation, safety of operations, prognostics and even forensic analyses.

Being an emerging technology, several challenges still need to be tackled in order to make UAS suitable for

real-world applications, which impose strict performance, dependability and privacy requirements. In the light

of the above, this paper provides an in depth survey of current UAS technologies for Beyond the Visual Line of

Sight (BVLOS) UAS operations and highlight the main technological challenges and requirements that arise.

We also focus on the emerging and future BVLOS UAS features and the technological advances that render

their expansion in various industrial sectors promising.

1 INTRODUCTION

Unmanned Aerial Vehicles (UAVs), commonly re-

ferred to as drones, are the main component of Un-

manned Aerial Systems (UAS), which also comprise

a ground-based controller, and communication sys-

tem. UAVs were ﬁrst introduced as military devices,

but soon managed to take a leap in the commercial

and civil sector. In the last few years, UAVs are in-

creasingly considered in a wide range of applications

for surveillance and safety checks in domains such as

construction, mining, agriculture, logistics and prod-

uct delivery, insurance, and many more (Nouacer

et al., 2020). As their popularity is increasing, it is

predicted that the global commercial drone’s market

will grow to 7.13 billion at a CAGR of 19.9 through

2022 (Kovalev et al., 2019). To this end, UAS use

is expected to have a signiﬁcant impact on the qual-

ity of life, health, social and economic well-being

(Kyrkou et al., 2019). In this direction, Beyond Vi-

sual Line of Sight (BVLOS) capabilities are becom-

https://orcid.org/0000-0001-8795-5560

https://orcid.org/0000-0003-4366-6470

https://orcid.org/0000-0002-0876-8167

https://orcid.org/0000-0002-7424-8557

ing recently a pivotal aspect for the drone industry.

The extended levels of autonomy in addition to the

increased efﬁciency of such operations has given po-

tential to even more applications in the ﬁeld. In the

rest of the manuscript, the terms Unmanned Aerial

Vehicle (UAV) and drone are used interchangeably to

refer to an unmanned vehicle that is remotely oper-

ated by a human or software.

The related literature so far provides useful in-

formation for the technological aspects of UAS, the

societal and regulatory barriers for their acceptance

and forms a useful basis for a similar analysis for

BVLOS drone operations. Authors in (Hassanalian

and Abdelkeﬁ, 2017) provide a detailed analysis of

the various drone types, with emphasis on their ca-

pabilities and restrictions. The main types of UAS

applications are surveyed in (Rakha and Gorodetsky,

2018) and in (Otto et al., 2018), authors provide an

overview of current optimization approaches for civil-

drone applications. The recent research efforts on

the use of UAVs in transportation, and speciﬁcally

in road safety, trafﬁc monitoring and highway infras-

tructure management tasks are surveyed in (Outay

et al., 2020). Finally, more interesting applications

of UAS integration in smart cities, as well as the en-

Politi, E., Panagiotopoulos, I., Varlamis, I. and Dimitrakopoulos, G.

A Survey of UAS Technologies to Enable Beyond Visual Line Of Sight (BVLOS) Operations.

DOI: 10.5220/0010446905050512

In Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2021), pages 505-512

ISBN: 978-989-758-513-5

505

Figure 1: An overview of the challenges, requirements and enablers, for BVLOS drone operations.

abling technologies and issues are explored in (Mo-

hamed et al., 2020).

Existing surveys emphasize on remote controlled

UAVs, in which the operator has a visual line of

sight to the vehicle and navigates the drone from a

ground based controlled, using the communication

system. The technological advances and the increased

demand for drone operations, give rise to the need

for UAS that can successfully perform BVLOS op-

erations, with wider autonomy and minimised inter-

action with the ground control. This work surveys the

current state of the art on BVLOS drone operations,

and emphasizes on technologies that can support the

related projects. It analyses each technology and lists

the high and low level requirements that unmanned

operation of UAS BVLOS dictates.

The main contributions of this work can be sum-

marized in the following and Figure 1 depicts the

main points of this analysis:

• A presentation of the main BVLOS operation

challenges and the requirements they raise, with

emphasis on the technological requirements.

• A survey of the main BVLOS advances and future

scenarios and the main technology enablers that

can support them.

To this end, Section 2 summarizes the main survey

works in BVLOS drone operations. Section 3 refers

to the main tasks and challenges for BVLOS opera-

tions and summarizes the high and low-level require-

ments that are accomodated. Section 4 presents the

main technologies needed for the successful delivery

of BVLOS operations and presents the key enablers

for future BVLOS drone operation scenarios. Finally,

in Section 5 we discuss the main ﬁndings of this study

and the conclusion of this work.

2 RELATED WORK

The integration of BVLOS capabilities in various

drone operations is lately attracting more research in-

terest. Although there is a wide range of applica-

tions traditionally supported by Visual Line of Sight

(VLOS) and Extended Visible Line of Sight (EVLOS)

operating modes, BVLOS operations are expected to

dominate our skies within the next years, offering a

large variety of services, such as inspection of infras-

tructure, deliveries, human transportation or precision

agriculture (Undertaking, 2018).

The three modes depend on the interaction be-

tween the UAV and its operator (Sebbane, 2018):

• In VLOS the UAV should always be within the in-

obstructed view of the pilot (Macias et al., 2019).

• In EVLOS the operator may partly rely on critical

ﬂight information from remote observers that are

in visual line with the UAV (Bloise et al., 2019).

• In BVLOS the UAV is allowed to operate away

from the visual range, based on instrumentation

such as on-board cameras and detect-and-avoid

technologies.

The choice of the appropriate operation mode de-

pends on the type of application, the distance that can

or must be covered, the conditions in the operation

spot and in some cases on the criticality of the task.

This makes VLOS mostly preferable by hobbyists,

real estate agents, cinematographers and TV produc-

ers for scene coverage, EVLOS and BVLOS a better

choice for inspections and surveying (structural, mil-

itary, environmental or agricultural), mapping as well

as for package delivery and search and rescue mis-

sions (Davies et al., 2018).

In the absence of human control for short or longer

periods, recent works aim to explore BVLOS modes

VEHITS 2021 - 7th International Conference on Vehicle Technology and Intelligent Transport Systems

506

that endow UAV ﬂights with higher levels of intel-

ligence and greater efﬁciency. Compared to VLOS

or EVLOS operation modes, which require a certain

level of human interaction, BVLOS UAVs can dy-

namically change their ﬂight plan and mission accord-

ing to prevailing conditions without a human operator.

Extended autonomy in BVLOS capabilities enables a

drone to cover far greater distances, with a lower cost

and a reduced risk to human life. On the other side,

BVLOS operations create a new landscape for com-

munication, navigation, and ﬂight under varying con-

ditions. Various BVLOS scenarios for efﬁcient capa-

bilities are explored in (Fang et al., 2018).

During the last few years, a number of inter-

esting studies propose novel methodologies for BV-

LOS missions and operations in numerous applica-

tions (Kato et al., 2019). In this basis, BVLOS mis-

sions enable service providers to perform complex

operations by data provided from on-board and exter-

nal instruments. The operator is informed about the

position, altitude, speed and direction of ﬂight as well

as about all the relevant parameters of the ﬂight body.

In addition, UAS ﬂying in BVLOS operation mode

can also change control sensors and ﬂight parameters

to collect data (Davies et al., 2018).

This work presents the main challenges for BV-

LOS operations and the requirements that emanate

from them. Next, we identify the technological ad-

vances that may play a key role as enablers for the

deployment of successful BVLOS drone scenarios.

3 BVLOS MAIN CHALLENGES

Security and Safety: Security and safety of ﬂight re-

main critical issues in unmanned aircraft missions. It

is clear that the absence of a clear regulatory frame-

work at national or international level (e.g. for China,

the US or EU countries) inhibits the growth of the

drone services and aircrafts market, and limits the po-

tential for employment creation in this sector of the

economy (Nouacer et al., 2020). Therefore, across

the globe, laws and regulations are needed in order to

manage drone impacts, particularly in lower airspace

(Merkert and Bushell, 2020). Regulatory measures

can signiﬁcantly increase the requirements of oper-

ators to build a safety culture into their operations.

To this end, the European Aviation Safety Agency

(EASA) has developed a regulatory framework that

deﬁnes the technical and operational requirements for

UAS, provides guidelines for safe operation, and ad-

dresses privacy, security and data protection issues

(Bassi, 2019). Standards and Recommended Prac-

tices (SARPs) for BVLOS operations are under de-

velopment by the International Civil Aviation Organi-

zation (ICAO) with adoption foreseen in 2020 leading

to operations as from 2023 (Undertaking, 2018).

Route Planning and Navigation: Efﬁcient navi-

gation and perception of the UAV surroundings is

critical in BVLOS operations. Amongst other au-

tonomous features, a UAV operating BVLOS should

be able to dynamically revise its path planning strat-

egy according to the environment and through a "De-

tect Sense and Avoid" (DAA) system, that guaran-

tees collision avoidance and situational awareness

(González-Sieira et al., 2020).

To improve the planning efﬁciency of UAS, many

innovative methods have been explored, such as

multi-resolution maps (González-Sieira et al., 2020),

game theory, and bio-inspired methods, such as

swarm optimization algorithms and Potential Fields

(Iacono and Sgorbissa, 2018). In latest years, the in-

tegration of Artiﬁcial intelligence technologies (i.e.

Deep Learning/Machine Learning) has thrown spot-

light on drone intelligence and automation, endow-

ing UAV applications with a higher degree of robust-

ness and accessibility (Nouacer et al., 2020). Sev-

eral very interesting studies have explored various AI

methods, such as Reinforcement Learning (RL) algo-

rithms in combination with deep learning techniques

to efﬁciently execute navigation tasks in large-scale

complex environments (Wang et al., 2019)

Communication: During a mission, it is essential

for an UAV to interact with other entities, such as air

trafﬁc management systems, ground stations or even

other UAVs. In BVLOS operations, there exists a

greater need for a UAV to be aware of its surround-

ings with the use of DAA technology (Davies et al.,

2018). In such terms, robust and reliable communi-

cation channels as well as efﬁcient data exchange are

essential for safe and efﬁcient operations.

Existing cellular networks (including the 5G) or

even satellite links may support data exchange in BV-

LOS applications (Hosseini et al., 2019). However

several issues may compromise the reliability of com-

munication between operator and UAV. For instance,

long-distance radio communication may impose large

propagation delay, high packet-loss ratio, and high

power consumption. Moreover, the kinematics of the

UAV leads to time-variant network topologies and fre-

quent link outages, that often lead to communication

failure(Wang et al., 2017). It is thus important to de-

velop communication protocols and communication

loss handling techniques that will guarantee the unin-

terrupted UAV operation.

Object Detection and Collision Avoidance: As avi-

ation technology is progressing, the unique character-

istics of UAS, as ﬂying instruments with high mobil-

A Survey of UAS Technologies to Enable Beyond Visual Line Of Sight (BVLOS) Operations

507

ity in three-dimensional space and the need for au-

tonomous operation, raise new requirements of vigi-

lant path planning strategies, that can safely navigate

drones from origin to destination. One of the most

challenging aspects of a UAV mission is to combine

autonomous features with an optimal motion planning

approach, that guarantees a safe navigation through

unknown spaces and obstacles, that may appear dy-

namically as the route evolves. The main challenge

for current collision avoidance systems for drones is

the effective and efﬁcient detection of static or mov-

ing objects, the identiﬁcation of their type and the

prediction of their trajectory. With this information,

collision avoidance systems are able to predict trajec-

tories that will meet in space and time, and conse-

quently change the drone speed and direction in order

to avoid it.

In such terms, UAVs operating BVLOS must have

the ability to dynamically revise their course and

safely change paths, in order to provide conﬂict-free

trajectories through a DAA capability (Krishnan and

Manimala, 2020).

Requirements for BVLOS Operations: Recent de-

velopments in aviation technology are driving new

business opportunities for UAS, particularly in BV-

LOS operations. As the future integration of drones is

expected to rely on high levels of automation and con-

nectivity, the establishment of speciﬁc requirements

and procedures to ensure safety in the air, as well as

on the ground, is critical. In order to offer safe and

efﬁcient BVLOS missions, several requirements need

to be addressed to ensure the maximum safety for BV-

LOS operations. It is important to improve the UAS

communications technology, in order to support re-

mote command and control, navigation, surveillance,

and situation awareness. This will also allow the in-

tegration with Air Trafﬁc Management (ATM) sys-

tems that will remotely pilot UAVs, and will open

the road for autonomous or semi-autonomous ﬂights

(Balachandran et al., 2017).

Aviation safety and privacy requirements should

also be considered. UAVs should operate with mini-

mum risk to other airspace users, and people on the

ground, especially in the highly cluttered airspace

of urban areas. Moreover, privacy in terms of data

protection of both the operators and their customers

should be sustained. Environmental protection is an-

other critical issue in UAS operations (Undertaking,

2018). The impact of drone trafﬁc on the environ-

ment, such as emissions, noise, visual pollution and

air quality can affect the health and quality of life of

citizens and therefore the aviation sector should re-

spond to the major environmental challenges ahead

with innovative, smart and environmentally sustain-

able solutions and technologies.

4 BVLOS TECHNOLOGY

ADVANCES AND ENABLERS

As drones are increasingly considered for a number of

applications in diverse areas, it is generally expected

that their ubiquity will signiﬁcantly expand within the

next few years. The use of UAVs can bring signiﬁcant

economic savings and environmental beneﬁts, while it

can reduce the risk to human life. Recent advances in

drone technologies, as well as the existence of a clear

regulatory framework can set the ground for a greater

adoption of unmanned technology in a wide range of

applications. Several key areas have been identiﬁed

as facilitators of future growth and development for

drones(Nouacer et al., 2020), and are analyzed in the

following.

Flight Control: The design of reliable and high-

performance ﬂight control systems can be a difﬁcult

challenge for many reasons, such as unpredictable dy-

namics (e.g. air ﬂows or rain) that may affect the

ﬂight of small UAVs, or the presence of static and

moving obstacles in cluttered urban environments that

can pose severe limitations to aircraft navigation, etc.

(Santoso et al., 2017).

An aircraft autopilot system allows the aircraft

control without direct human interaction, reducing

operation errors and the work load of human pi-

lots. Such systems handle most of the time-intensive

non–decision-making tasks, helping the human pilots

to focus on the overall status of the aircraft and ﬂight

(Jia et al., 2018). There exist two levels of autonomy

for ﬂight-control systems (Aber et al., 2019):

• Autonomous or fully automated mode: In this

mode, the aircraft follows a ﬂight-line that has

been predeﬁned by the user with ﬂight-planning

software. It makes its own decisions during the

mission and reacts to unforeseen events without

the pilot’s intervention.

• Assisted or semi-automated mode: In this case,

human intervention is reduced to a minimum

(speed and direction control) allowing the pilot

to perform complex decision processes and bet-

ter concentrate on high added-value tasks, such as

safety of the ﬂight.

Recent advances in autopilot systems focus on

more intelligent approaches of adaptive control tech-

nologies that can sustain a higher degree of autonomy

during ﬂight and therefore deal with various environ-

mental uncertainties as well as on-board limitations

(Santoso et al., 2017). Moreover, demands for so-

VEHITS 2021 - 7th International Conference on Vehicle Technology and Intelligent Transport Systems

508

phisticated decision making and cognitive capabilities

in current aviation require computationally efﬁcient

and robust approaches. To this end current research

trends have explored the implementation of fuzzy

logic based control techniques (Xie et al., 2019), arti-

ﬁcial neural networks (Boutemedjet et al., 2019), ge-

netic algorithms (Mousavi et al., 2019) or swarm in-

telligence (Dasdemir et al., 2020).

Command and Control: Ensuring a reliable Com-

mand and Control (C2) link is essential for safe BV-

LOS drone operations. The purpose of this two-way

link is to provide a secure and reliable communi-

cation between the remote pilot ground station and

the aircraft, which will allow to manage a secure

and effective ﬂight. On one hand, in the uplink, i.e.

from a drone to base station (BS), the control link is

used to update the Unmanned Aircraft System Traf-

ﬁc Management (UTM) or ﬂight control unit with the

drone location, and provide information necessary for

the control function decision making. On the other

hand, the downlink (i.e. communications towards the

drone) allows the control function to change the drone

direction and speed accordingly, in order to avoid ob-

stacles or send commands to various on-board sen-

sors(Nguyen et al., 2017). Existing cellular networks

(e.g. LTE systems) are a natural candidate to provide

C2 link for drone operations. However, several lim-

itations may occur due to the growing bandwidth re-

quirements or interference at high altitude (Nguyen

et al., 2017). Moreover, different channel conditions

and frequencies of BVLOS operations, with different

latency and range, increase the challenges for a reli-

able communication(Hosseini et al., 2019).

To meet these challenges, other technologies that

offer new capabilities are explored. For example, the

millimeter wave bands that are deployed in 5G cellu-

lar networks offer larger bandwidths that allow faster

payload communications. The use of satellite con-

nections may also efﬁciently complement and extend

the coverage and reliability for BVLOS links. How-

ever, the choice of satellite orbit, i.e., low-earth orbit-

ing (LEO) or geosynchronous earth orbiting (GEO)

may be critical (Kodheli et al., 2017) in this task.

Scene Perception with Limited Resources: Future

drone technology is currently undergoing ground-

breaking progressive improvement. Scene perception

is becoming one of the most critical tasks for safe and

accurate drone navigation operations. Apart from the

detection of individual objects that may interfere as

obstacles to the vehicle root, perception also refers

to the understanding of their relative locations, and

their tracking in order to predict their future behavior.

It also includes the detection of environmental con-

ditions (e.g. wind) that may affect the route of any

moving object, including the drone itself.

Since UAS missions employ multiple image sen-

sors in the visible or infrared (for nightly operations)

spectrum, the main requirement is the smart fusion

of multiple sensors (Carrio et al., 2020) in an re-

source efﬁcient manner that allows very fast detection

of moving objects and their distance from the moving

drone as well as the separation from the background.

The fusion of multiple sensors and the process-

ing of RGB and stereoscopic images with deep neural

network (NN) architectures has been proven beneﬁ-

cial for scene perception tasks with several applica-

tions. For this reason, deep NNs are becoming the

main solutions for such tasks and ﬁeld-programmable

gate array (FPGA) implementations are used to facili-

tate real-time object detection tasks on mobile devices

(Xu et al., 2018). The increased processing capabili-

ties of such edge devices allow to design and imple-

ment distributed processing scenarios, that combine

heavy centralised trained deep learning models with

lighter or compressed versions on the edge for infer-

ence (Chmaj and Selvaraj, 2015). Transfer learning

techniques are recently employed to leverage training

on the edge (Anwar and Raychowdhury, 2020).

Collective Security and Safety of Drone

Operations: Guaranteeing the safe and secure

navigation of individual drones, under the current

constraints of computational power and storage,

may become a really hard task. A solution to the

increased processing requirements that real-time

scene and environment perception sets for individual

drones, can be the collective intelligence of drone

ﬂeets (Akram et al., 2017). Drones that exchange

information about the scene on air can signiﬁcantly

reduce the overall processing load and lead to safer

navigation plans.

In addition to the above, lightweight (cryp-

tographic) protocol designs will provide security

solutions for resource and energy-constrained drones.

Future scenarios build on the Internet of Drones

(IoD), but still lack of efﬁcient data encryption tech-

niques that can scale to the computational capability

of drones (Lin et al., 2018). Under the new condi-

tions, access controls and precise navigation plans of

drones are replaced with plans comprising smaller

hops towards the destination and real-time navigation

adjustments to avoid congestion and collisions.

Sensors: There is an obvious need for a UAV to be

aware of its surroundings and aware of other air traf-

ﬁc. The rapid development of sensor technologies

combined with advances in the miniaturization of in-

struments and data systems have opened up new po-

tential in UAVs’ sensing capabilities. For instance,

the integration of GPS and detection sensors can al-

A Survey of UAS Technologies to Enable Beyond Visual Line Of Sight (BVLOS) Operations

509

low compact and robust navigation solutions to deter-

mine attitude and location of vehicle, so it can de-

termine its state in a robust way and use appropri-

ate control techniques for autonomy (García et al.,

2020). Apart from navigation, UAVs can perform

sophisticated data gathering due to various on-board

sensors, such as capturing atmospheric or agricultural

data (van der Merwe et al., 2020). One major tech-

nological breakthrough over the past years is the ﬁeld

of Artiﬁcial Intelligence (AI)-based methods, which

leverage adaptive capabilities and enhance percep-

tion tasks, such as object detection, classiﬁcation, and

scene segmentation (Bijjahalli et al., 2020).

Efﬁcient Power Storage and Distribution: As UAV

operations are characterized by limited on-board re-

sources, energy optimization is important. Several

factors can be energy consuming during a ﬂight, for

instance transmission and reception of data, execu-

tion of software functions resource management or

ﬂight time optimization(Wang et al., 2020). More-

over UAVs may consume large amounts of propul-

sion power in order to accelerate, maintain airborne

or perform hovering tasks. Recent developments in

rechargeable battery cells, super-capacitors and solar

cells aim to offer an extension to the ﬂying time of

UAVs by increasing the life cycle of battery. More-

over a lot of effort has been put in order to improve

the throughput and energy consumption, by optimiz-

ing the trajectory and power allocation of UAV. Re-

cent works have also explored UAVs energy opti-

mization by considering both propulsion energy and

wireless communication energy, while ensuring satis-

factory communication requirements with the ground

stations (Amorosi et al., 2018).

5 DISCUSSION AND

CONCLUSIONS

The survey of current technology advances and fu-

ture enablers for UAS operations reveals that there are

many promising research results, which can support

BVLOS missions and help to align with the regula-

tory frameworks for ﬂight and operational safety.

Modern UAS autopilot systems use intelligent ap-

proaches that adapt to the environmental conditions

and to the fused input of sensors, thus adding to

their autonomy during the ﬂight and allowing them

to cover longer distances without the need of ground

control or VLOS supervision. Similar to autonomous

vehicles, which ask for human intervention only when

the conditions do not allow for a clear decision, au-

tonomous UAS are developed to operate without or

with limited human intervention. This limits the need

for air-to-ground communication and consequently

minimizes the power and the bandwidth consumed

for communication and remote control. Even when a

connection with a ground station is required, the new

5G cellular networks promise speed improvement and

right trade-offs between speed, latency, and cost.

Furthermore, as UAS operations are characterized

by limited on-board energy, due to the vehicles’ size

and weight constraints, energy optimization is crucial

for the performance and execution of UAS missions.

Recently, FPGAs are gaining the race over GPUs in

clearly deﬁned machine vision tasks, since hardware

is much faster than software. They lack the ﬂexibil-

ity of GPUs and need more time to reprogram or ﬁne

tune, but have signiﬁcantly lower energy consump-

tion, and can be used to accelerate smaller computer

vision tasks, such as obstacle detection.

One of the most important risks for the wide adop-

tion of drones is related to their safe and secure op-

eration. Following the advances of the automotive

industry, it is critical to deﬁne similar industry-wide

frameworks for safety, that guarantee the conformity

of UAVs and UAS to the standards, and certiﬁca-

tions of the underlying regulatory framework. In or-

der to efﬁciently address this challenge, it is of cru-

cial importance to create adequate real-world tests

and/or laboratory simulations for BVLOS operations

enabled by the aforementioned technologies that they

represent, being able to support a wide range of civil-

ian and military scenarios. Following methodologies

for human-machine corroboration, such as the cor-

roborative V &V (veriﬁcation and validation) work-

ﬂow presented in (Webster et al., 2020) it would be

possible to pass from formal veriﬁcation scenarios,

to simulation-based testing and then to real experi-

ments. The knowledge resulting from such scenar-

ios will support decision-making and development of

technology road-maps based on robust future technol-

ogy assessment. Furthermore, this knowledge will

lower the barriers for end users to adopt the BVLOS

drone technologies, and obtain new and unforeseen

services at more manageable costs and effort.

Although UAS in general are a major technolog-

ical breakthrough, there are still several factors that

impede their adoption. The greatest challenge to the

widespread integration of UAS by the society is pub-

lic acceptance, since such operations raise novel and

valid concerns in terms of safety and privacy

. Pub-

lic acceptance is also subject to various concerns over

the safety of UAV ﬂights over civilian air space, the

environmental disruption and the privacy of sensitive

information.

This article surveyed the main BVLOS drone op-

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VEHITS 2021 - 7th International Conference on Vehicle Technology and Intelligent Transport Systems

510

eration challenges an the requirements emerging from

them, with an emphasis on the technology aspects.

The article also surveyed the main technology ad-

vances that will play a critical role in the expansion

of BVLOS drone operations in the near future.

Despite all the technology advances regarding the

UAS operations, some open issues still need to be in-

vestigated, such as positioning, situation awareness,

risk detection and avoidance, ﬂight investigation, and

energy consumption minimization. Apart from the

technology challenges and solutions there are also

several societal and regulatory challenges that must

be met. A concrete regulatory framework for BVLOS

operations must be formally deﬁned, veriﬁed and vali-

dated, bringing trustful human-machine collaboration

in the front. On this basis, one of the most important

issues that could be addressed in the future, regarding

the BVLOS UAS provided services, is to establish ap-

propriate privacy and security mechanisms.

An in depth study of the legal, regulatory and

safety frameworks is among the next plans of our

work. Theoretical methodologies that have been

used for the formalisation of autonomous agents and

frameworks that have been tested in the automotive

industry will be examined in order to carefully de-

ﬁne a trustworthy process for designing and deliver-

ing BVLOS operations.

ACKNOWLEDGEMENTS

This work is a part of ADACORSA project, that has

received funding from the ECSEL Joint Undertaking

(JU) under grant agreement No 876019. The JU re-

ceives support from the European Union’s Horizon

2020 research and innovation programme and Ger-

many, Netherlands, Austria, Sweden, Portugal, Italy,

Finland, Turkey national Authorities.

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